3.0

credits

Average Course Rating

Discusses data management techniques (e.g. cleaning, outliers) and implementation. Applies descriptive and intermediate quantitative data analysis using large-scale data from low-and middle-income settings or from global agencies. Examines the application of quantitative methods (including their associated strengths and limitations) with a focus on how these are influenced by varied LMIC settings and underserved populations. Supports second-year MSPH students to conduct their own analysis on test datasets in R/STATA/others.